Influence of study characteristics, methodological rigour and publication bias on efficacy of pharmacotherapy in obsessive-compulsive disorder: a systematic review and meta-analysis of randomised, placebo-controlled trials

Question We examined the effect of study characteristics, risk of bias and publication bias on the efficacy of pharmacotherapy in randomised controlled trials (RCTs) for obsessive-compulsive disorder (OCD). Study selection and analysis We conducted a systematic search of double-blinded, placebo-controlled, short-term RCTs with selective serotonergic reuptake inhibitors (SSRIs) or clomipramine. We performed a random-effect meta-analysis using change in the Yale-Brown Obsessive-Compulsive Scale (YBOCS) as the primary outcome. We performed meta-regression for risk of bias, intervention, sponsor status, number of trial arms, use of placebo run-in, dosing, publication year, age, severity, illness duration and gender distribution. Furthermore, we analysed publication bias using a Bayesian selection model. Findings We screened 3729 articles and included 21 studies, with 4102 participants. Meta-analysis showed an effect size of −0.59 (Hedges’ G, 95% CI −0.73 to −0.46), equalling a 4.2-point reduction in the YBOCS compared with placebo. The most recent trial was performed in 2007 and most trials were at risk of bias. We found an indication for publication bias, and subsequent correction for this bias resulted in a depleted effect size. In our meta-regression, we found that high risk of bias was associated with a larger effect size. Clomipramine was more effective than SSRIs, even after correcting for risk of bias. After correction for multiple testing, other selected predictors were non-significant. Conclusions Our findings reveal superiority of clomipramine over SSRIs, even after adjusting for risk of bias. Effect sizes may be attenuated when considering publication bias and methodological rigour, emphasising the importance of robust studies to guide clinical utility of OCD pharmacotherapy. PROSPERO registration number CRD42023394924.


In-and exclusion of studies.
BMJ Publishing Group Limited (BMJ) disclaims all liability and responsibility arising from any reliance Supplemental material placed on this supplemental material which has been supplied by the author(s) With full-text screening, we excluded 23 studies for using the same data from a trial that had already been presented in an earlier paper.We excluded eight studies for not using the YBOCS scale as outcome measure and seven for not using a placebo control group.17 were excluded because they were a review or comment and three for presenting a case report.Three papers did not provide enough efficacy data to include them in our review, even after requests for information.We excluded one study for using 24 hours as endpoint, after administering intravenous clomipramine.

Risk of bias assessment.
We used the https://methods.cochrane.org/risk-bias-2,and through the official guidance document we filled in the risk of bias template for each study.See table S1 , in which we simplified and summarized our risk of bias assessment.

Meta-regression analysis
For studies included in our multiple metaregression, we used a multicollinearity test in order to avoid overfitting, whereby studies with a high correlation (r>0.8) would be excluded from the multiple metaregression.As table S2 shows, no studies were correlated to the degree of redundancy.

Table S2: multicollinearity testing
Using anova, we compared performance and correctness of fit of the different multiple meta-regression models.The multiple metaregression using clomipramine and high risk of bias performed significantly better than individual regression models (see table S3).Further increasing model complexity did not lead to a significantly better performance.Corrected Akaike's information criterion was lowest for the model using clomipramine and high risk of bias (see table S4).Using the parsimony principle, the metaregression with high risk of bias and clomipramine was preferred over more complex models.Notable, furthermore, is that even when using the most complex model including all metaregression variables, clomipramine remained a significant predictor (beta -0.39, 95%CI -0.70 to -0.076, p = 0.017).

Trial arms
Sponsor

Meta-regression of SSRI studies
As described in our main analysis, heterogeneity was low across SSRI studies (I squared = 16.0%,tau < 0.0001), and the test for heterogeneity was not significant (Q = 30, p = 0.23), suggesting the effect of SSRIs

Publication bias
We used the robustbayesiancopas package in order to perform our Bayesian analysis of selection bias and used their proposed methods.We used multiple assumptions about distribution of the random effect (Student's T, Laplace, normal and slash distributions).Then, we extracted the Deviance Information Criterion (DIC) for each model to compare their goodness of fit.As slash distributions had the best fit (i.e. the lowest DIC), we used this distribution in further calculations.,We then estimated the correlations parameter and fit a Bayesian model with and without correction for bias.We repeated our analysis multiple times using different seed settings which did not change the results.For SSRI studies only, using a Bayesian Copas selection model, we found a moderate effect of publication bias (D = 0.48) similarly to the full sample, with a decrease of 0.077 SMD, from -0.48 (95% credible interval -0.57 to -0.40) to -0.41 (95% credible interval -0.54 to -0.22).
BMJ Publishing Group Limited (BMJ) disclaims all liability and responsibility arising from any reliance Supplemental material placed on this supplemental material which has been supplied by the author(s)

Sensitivity analysis
After fully excluding all studies with a high risk of bias, clomipramine was still associated with a higher effect size (-0.38,p = 0.028, 95% CI =-0.72 to -0.044), emphasizing the robustness of our finding that clomipramine has a higher efficacy than SSRI's when compared to placebo.
After combining intervention arms using different fixed doses, efficacy measures were comparable (SMD = -0.65,95% CI -0.83 to -0.46).See figure S3 for forest plot, including measures of heterogeneity.Furthermore, outcomes of meta-regression remained largely unchanged, except non-significance of the amount of intervention arms that were used.As our original analysis method increases the relative weight of studies with multiple intervention arms, the fact that in this analysis intervention arms are not significantly related to efficacy is an important addition to our original fidings.Please see table S5 for single meta-regression results, and table S6 for multiple metaregression including high risk of bias and clomipramine use.
Furthermore, precision of estimates broadly decreased, with higher p-values, which is understandable considering the combination of doses decreases the degree of freedom for meta-regressions.

Figure
Figure S3forest plot of studies with fixed doses combined in a single intervention arm.

Table S4 : Akaike's information criterion of metaregressions Variables in regression model AICc
BMJ Publishing Group Limited (BMJ) disclaims all liability and responsibility arising from any reliance to be consistent across studies.Meta-regressions for different SSRI's were not significant.Results persisted when considering a prediction interval (95% PI -0.55 to -0.39).

Table S5
single regression outcomes for combined fixed doses.BMJ Publishing Group Limited (BMJ) disclaims all liability and responsibility arising from any reliance Supplemental material placed on this supplemental material which has been supplied by the author(s) There were serious limitations due to most studies being at moderate risk of bias.Results were inconsistent, but less so for SSRI's.Outcomes were direct, meaning population, intervention, or outcomes are comparable.BMJ Publishing Group Limited (BMJ) disclaims all liability and responsibility arising from any reliance Supplemental material placed on this supplemental material which has been supplied by the author(s)